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Record W2922516182 · doi:10.1257/aeri.20190114

Long-Run Effects from Comprehensive Student Support: Evidence from Pathways to Education

2020· article· en· W2922516182 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAmerican Economic Review Insights · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsReceiptEarningsDisadvantagedCoachingWelfareIncentiveSample (material)Educational attainmentDemographic economicsEconomicsPropensity score matchingMatching (statistics)Public economicsBusinessLabour economicsEconomic growthAccounting

Abstract

fetched live from OpenAlex

Offering comprehensive education support services to disadvantaged students shows promise for improving academic attainment. We explore longer-term impacts of the Pathways to Education program, a set of coaching, tutoring, group activities, and financial incentives initially offered in 2001 to grade-nine students living in the largest public housing community in Toronto. Using a difference-in-difference methodology and matching school records to income tax data through age 28 for a sample of students living in public housing under similar circumstances, we find that Pathways eligibility increased adult annual earnings by 19 percent, employment by 14 percent, and reduced welfare receipt by more than 30 percent. (JEL I22, I23, I24, I26, I28, L31)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.073
GPT teacher head0.344
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it